Kelp vs Urchins
Nick Toimieri
sys.date()
1 Triggers and settings
2 Import Data
Note: for Neah Bay in 2016
- There are not algae data for the South Area only, the North.
- There are are only two transects of invert data for the North. There are 5 transects in the South area.
3 By KELP SPECIES but summed across all urchins
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.1 Individual plot version
The following splits the facet into individual plots for better plotting and labeling.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
3.2 Site x Year regressions for urchins vs kelp
##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Tatoosh Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.1701 -0.4489 -0.3264 0.4759 1.7600
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.2596 0.6863 1.835 0.116
## Urchins 0.2734 0.4624 0.591 0.576
##
## Residual standard error: 0.9967 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.05507, Adjusted R-squared: -0.1024
## F-statistic: 0.3497 on 1 and 6 DF, p-value: 0.5759##
## Call:
## lm(formula = Kelp ~ Urchins, data = nereo[nereo$site == "Destruction Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.8096 -0.6230 0.1658 0.3656 0.9937
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.8959 0.2921 3.067 0.022 *
## Urchins -0.4154 0.9947 -0.418 0.691
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7023 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.02824, Adjusted R-squared: -0.1337
## F-statistic: 0.1744 on 1 and 6 DF, p-value: 0.6908##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Tatoosh Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.6767 -0.3926 -0.1239 0.2134 1.2084
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.6660 0.4413 1.509 0.1820
## Urchins 0.7362 0.2973 2.476 0.0481 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6408 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.5054, Adjusted R-squared: 0.4229
## F-statistic: 6.13 on 1 and 6 DF, p-value: 0.04807##
## Call:
## lm(formula = Kelp ~ Urchins, data = ptery[ptery$site == "Destruction Island",
## ])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.3101 -0.1073 0.0115 0.1770 0.1871
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.52912 0.08321 6.359 0.000709 ***
## Urchins -0.16689 0.28336 -0.589 0.577369
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2001 on 6 degrees of freedom
## (1 observation deleted due to missingness)
## Multiple R-squared: 0.05465, Adjusted R-squared: -0.1029
## F-statistic: 0.3469 on 1 and 6 DF, p-value: 0.57744 Total for each.
I know we’re not supposed to combine macro & nereo but…just to see
## `summarise()` has grouped output by 'site', 'year', 'zone', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site'. You can override using the
## `.groups` argument.
5 BY SPECIES
5.1 Transect level, all depths
##
## Attaching package: 'cowplot'## The following object is masked from 'package:ggpubr':
##
## get_legend## The following object is masked from 'package:lubridate':
##
## stamp## Loading required package: viridisLite
## By Site and Depth level
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 1020 7## [1] 340 5## [1] 255 5
correlation purple vs nereo at Tatoosh r = 0.2041619, p = 0.0609025
5.2 By Site and 5 m only
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.
## `summarise()` has grouped output by 'year', 'site', 'zone'. You can override
## using the `.groups` argument.## [1] 1020 7## [1] 340 5## [1] 255 5## $x
## [1] "Urchin density"
##
## $y
## [1] "Kelp density"
##
## $colour
## [1] "Site"
##
## attr(,"class")
## [1] "labels"
5.3 By site, averaged across depths, data = years
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.
## `summarise()` has grouped output by 'year', 'site'. You can override using the
## `.groups` argument.## [1] 540 7## [1] 180 4## [1] 135 4
## [1] NA## [1] NAThis plot compared to the previous is interesting.
At the transect level, there is a negative correlation between urchin density and kelp neroycystis density at Tatoosh
At the site level, there is a positive correlation for Nerocystis (r = NA) and for Pterogophora (r = NA)at Tatoosh across years.
6 TATOOSH
6.1 By transect
##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.97941 0.33652 5.882 8e-08 ***
## k -0.09710 0.06351 -1.529 0.13
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.952 on 84 degrees of freedom
##
## Number of iterations to convergence: 8
## Achieved convergence tolerance: 6.25e-06## a k
## 1.97940586 -0.09709903## [1] 363.0572
7 Across years
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8 Coastwide urchin - kelp patterns
8.1 All kelp: Nereo + Macro + Ptero
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor: r = 0.6501552; p = 0.0579929
8.2 Canopy only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.4459608
8.3 Nero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
8.4 Macro only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## Ptero only
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
cor r = 0.6206432; = 0.0745038
9 Tatoosh only
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.32144 0.14826 8.913 8.88e-14 ***
## k -0.09570 0.06814 -1.404 0.164
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9752 on 84 degrees of freedom
##
## Number of iterations to convergence: 4
## Achieved convergence tolerance: 2.746e-06## a k
## 1.32143739 -0.09570483## [1] 243.716
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.67860 0.25525 6.576 3.87e-09 ***
## k -0.01701 0.07368 -0.231 0.818
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.772 on 84 degrees of freedom
##
## Number of iterations to convergence: 4
## Achieved convergence tolerance: 1.173e-06## a k
## 1.67859810 -0.01701228## [1] 346.4706
## `summarise()` has grouped output by 'site', 'year', 'transect', 'area'. You can
## override using the `.groups` argument.##
## Formula: Y ~ a * exp(k * X)
##
## Parameters:
## Estimate Std. Error t value Pr(>|t|)
## a 1.7505 0.3054 5.733 1.51e-07 ***
## k -0.1064 0.1090 -0.976 0.332
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.997 on 84 degrees of freedom
##
## Number of iterations to convergence: 4
## Achieved convergence tolerance: 5.59e-06## a k
## 1.7505239 -0.1063911## [1] 366.9849
10 Combined Figure 5
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone'. You can
## override using the `.groups` argument.
## `summarise()` has grouped output by 'year'. You can override using the
## `.groups` argument.
## `geom_smooth()` using formula = 'y ~ x'
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
## Scale for y is already present.
## Adding another scale for y, which will replace the existing scale.
##
## Attaching package: 'gridExtra'
##
##
## The following object is masked from 'package:dplyr':
##
## combine
##
##
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
11 Kelp vs Kelp
## `summarise()` has grouped output by 'site', 'year'. You can override using the
## `.groups` argument.
Correlations between kelps
Macro vs Nereocystis, all sites r = -0.3496765 with p = 0.0185446
Macro vs Nereocystis, two sites r = -0.1516809 with p = 0.5479591
Macro vs Pterygophora, all sites r = 0.0080639 with p = 0.9580725
Macro vs Nereocystis, all sites r = 0.1160109 with p = 0.4479164
12 Correlations at Tatoosh Island across years (yearly means) for different depth zones
A different, and simplified version of the above for just tatoosh and faceted by species.
Essentially, there are different relationships at different depths. Probably too much detail for this manuscript.
## `summarise()` has grouped output by 'year', 'site', 'area', 'zone', 'transect'.
## You can override using the `.groups` argument.
## `summarise()` has grouped output by 'site', 'year', 'zone'. You can override
## using the `.groups` argument.